{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7ff5e465",
   "metadata": {},
   "source": [
    "## 任务2 对每个居民客户的用电缴费情况按照上述四种居民客户类型进行归类，结果保存为\n",
    "   ## ”居民客户的用电缴费习惯分析 2.csv”"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea56d4ec",
   "metadata": {},
   "source": [
    "### 1.1 导入相关python库"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "e624db6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from pylab import *\n",
    "import numpy as np\n",
    "import os"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59f77b50",
   "metadata": {},
   "source": [
    "### 1.2 探索数据"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eebfbfb4",
   "metadata": {},
   "source": [
    "数据来源于电力客户行为分析任务1输出的结果保存的数据'居民客户的用电缴费习惯分析 1.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5a994ce3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      user_id  平均缴费次数   平均缴费金额\n",
      "0  1000000001       8  123.375\n",
      "1  1000000002       7   70.000\n",
      "2  1000000003       7  168.571\n",
      "3  1000000004       8   77.625\n",
      "4  1000000005       7  214.286\n"
     ]
    }
   ],
   "source": [
    "data = pd.read_csv('居民客户的用电缴费习惯分析 1.csv')     # 读取excel文件\n",
    "print(data.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "475db9c9",
   "metadata": {},
   "source": [
    "#### 计算用户总平均缴费金额和总平均缴费次数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7f7672ff",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "总平均缴费金额为：105.842\n"
     ]
    }
   ],
   "source": [
    "maxmoney=0\n",
    "for i in range(0,100):\n",
    "    maxmoney+=data.iloc[i,2]\n",
    "avgmoney='%.3f'%(maxmoney/100)\n",
    "print(f\"总平均缴费金额为：{avgmoney}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8586b7ef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "总平均缴费次数为：7\n"
     ]
    }
   ],
   "source": [
    "maxtimes=0\n",
    "for i in range(0,100):\n",
    "    maxtimes+=data.iloc[i,1]\n",
    "avgtimes=round(maxtimes/100)\n",
    "print(f\"总平均缴费次数为：{avgtimes}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c143d3c",
   "metadata": {},
   "source": [
    "### 1.3对用户进行分类"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1932ccb8",
   "metadata": {},
   "source": [
    "依照标准为中国软件杯官网A5-电力客户行为分析 赛题业务场景模块所提供的标准，具体如下图所示："
   ]
  },
  {
   "attachments": {
    "tstmp_20220704163906.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "7307eca6",
   "metadata": {},
   "source": [
    "![tstmp_20220704163906.png](attachment:tstmp_20220704163906.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "de2983dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "a1=\"高价值型客户\"\n",
    "a2=\"大众型客户\"\n",
    "a3=\"潜力型客户\"\n",
    "a4=\"低价值型客户\"\n",
    "total=[]\n",
    "for i in range(0,100):\n",
    "    person=[]\n",
    "    person.append(data.iloc[i,0])\n",
    "    if data.iloc[i,1]>=avgtimes and data.iloc[i,2]>=float(avgmoney):\n",
    "        person.append(a1)\n",
    "    elif data.iloc[i,1]>=avgtimes and data.iloc[i,2]<float(avgmoney):\n",
    "        person.append(a2)\n",
    "    elif data.iloc[i,1]<avgtimes and data.iloc[i,2]>=float(avgmoney):\n",
    "        person.append(a3)\n",
    "    elif data.iloc[i,1]<avgtimes and data.iloc[i,2]<float(avgmoney):\n",
    "        person.append(a4)\n",
    "    total.append(person)\n",
    "names = [\"user_id\",\"用户价值类型\"]\n",
    "test = pd.DataFrame(columns = names,data=total)\n",
    "test.to_csv('居民客户的用电缴费习惯分析 2.csv',index=False,encoding='utf_8_sig')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46901bd3",
   "metadata": {},
   "source": [
    "对用户分类后的数据前5行为"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d10e6e60",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>用户价值类型</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1000000001</td>\n",
       "      <td>高价值型客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1000000002</td>\n",
       "      <td>大众型客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1000000003</td>\n",
       "      <td>高价值型客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1000000004</td>\n",
       "      <td>大众型客户</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1000000005</td>\n",
       "      <td>高价值型客户</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      user_id  用户价值类型\n",
       "0  1000000001  高价值型客户\n",
       "1  1000000002   大众型客户\n",
       "2  1000000003  高价值型客户\n",
       "3  1000000004   大众型客户\n",
       "4  1000000005  高价值型客户"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6aae79b2",
   "metadata": {},
   "source": [
    "### 1.4对用户价值类型不同客户的占比进行统计和相关可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3c999b94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>用户价值类型</th>\n",
       "      <th>不同客户的占比</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>用户价值类型</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>低价值型客户</th>\n",
       "      <td>20</td>\n",
       "      <td>0.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>大众型客户</th>\n",
       "      <td>41</td>\n",
       "      <td>0.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>潜力型客户</th>\n",
       "      <td>10</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>高价值型客户</th>\n",
       "      <td>29</td>\n",
       "      <td>0.29</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        用户价值类型  不同客户的占比\n",
       "用户价值类型                 \n",
       "低价值型客户      20     0.20\n",
       "大众型客户       41     0.41\n",
       "潜力型客户       10     0.10\n",
       "高价值型客户      29     0.29"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2=test.groupby(\"用户价值类型\").agg({\"用户价值类型\":\"count\"})\n",
    "df2[\"不同客户的占比\"]=df2[\"用户价值类型\"].apply(lambda x:x/np.sum(df2[\"用户价值类型\"]))\n",
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "10dc77e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#绘制不同类型客户的人数对比的条形图\n",
    "mpl.rcParams['font.sans-serif'] = ['SimHei']\n",
    "df2=df2.sort_values(by=\"不同客户的占比\",ascending=True)\n",
    "plt.figure(figsize=(6,4),dpi=100)\n",
    "x=df2.index\n",
    "y=df2[\"用户价值类型\"]\n",
    "plt.barh(x,height=0.5,width=y,align=\"center\")\n",
    "plt.title(\"不同类型客户的人数对比\")\n",
    "for x,y in enumerate(y):\n",
    "    plt.text(y+7,x,y,ha=\"center\",va=\"center\",fontsize=14)\n",
    "plt.xticks(np.arange(0,80,5))\n",
    "plt.tight_layout\n",
    "plt.savefig(\"不同类型客户的人数对比\",dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "f8e859cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#绘制不同类型客户人数占比图\n",
    "df2=test.groupby(\"用户价值类型\").agg({\"用户价值类型\":\"count\"})\n",
    "df2[\"不同客户的占比\"]=df2[\"用户价值类型\"].apply(lambda x:x/np.sum(df2[\"用户价值类型\"]))\n",
    "df2=df2.sort_values(by=\"不同客户的占比\",ascending=True)\n",
    "plt.figure(figsize=(7,4),dpi=100)\n",
    "x1=df2[\"不同客户的占比\"]\n",
    "labels=['低价值型客户', '大众型客户', '潜力型客户', '高价值型客户']\n",
    "colors=['#9999ff','#ff9999','#7777aa','#2442aa']\n",
    "explode=[0,0,0,0]\n",
    "patches,l_text=plt.pie(x1,labels=labels,colors=colors,explode=explode,startangle=90,counterclock=False)\n",
    "for t in l_text:\n",
    "    t.set_size(0)\n",
    "plt.axis(\"equal\")\n",
    "plt.legend(loc=(0.001,0.001),frameon=False)\n",
    "plt.title(\"不同类型客户人数占比图\")\n",
    "plt.savefig(\"不同类型客户人数占比图\",dpi=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49c5e995",
   "metadata": {},
   "source": [
    "综上所述，大众型客户人数最多，占有总数的41%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bb907f11",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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